(1) Field of the Invention
This invention relates to a method, an apparatus and a computer program for automated selection of image regions, and in particular (although not exclusively) for automated selection of regions of images of specimen tissue samples for histopathological assessment.
(2) Description of the Art
Selection of specimen tissue samples is an essential precursor to histopathological assessment of many forms cancer, anomalies or a patient's response. Once tissue samples have been selected, they may be assessed manually by a pathologist to determine parameters such as oestrogen and progesterone receptor (ER and PR) status, C-erb-2 and vascularity. C-erb-2 is also known as Cerb-B2, her-2, her-2/neu and erb-2. Automated histopathological assessment is also known: see e.g. published international patent applications WO 2004/017052, WO 2004/047004, WO 2004/046994, WO 2004/038633, WO 2004/057513, WO 2004/044845, WO 2004/055733 and WO 2004/072900.
Breast cancer in particular is a common form of female cancer requiring selection of tissue samples: once a lesion indicative of breast cancer has been detected, breast tissue samples are taken, chemically stained to bring out features of interest and assessed by a pathologist to establish a diagnosis, prognosis and treatment plan. Selection of tissue samples for assessment is however a time consuming manual process. It entails interpretation of colour images by human eye, which is highly subjective: a pathologist uses a microscope at low magnification to study a core biopsy specimen tissue sample on a microscope slide and identify parts of the slide which exhibit features suggesting that a parameter of interest is detectable. The objective is to identify regions (referred to as “tiles”) of the microscope slide image which are potentially suitable for determination of a histological parameter. A slide viewed at 2.5× magnification (typical for selection) corresponds to a maximum of 256 tiles at 40× magnification (typical for assessment) assuming no tile overlap, and many of these tiles may be unsuitable. Assessment time is wasted if tiles are selected in which it turns out that the parameter of interest is not in fact reliably detectable. The selection process is characterised by considerable variation between tiles selected by different observers, and even those selected by the same observer at different times. Moreover, there is a shortage of pathology staff, so it is desirable to automate the tile selection process.